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Commit 12d17835 authored by Eelco van der Wel's avatar Eelco van der Wel 💬
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Merge branch 'v4' into 'dev' 

V4

See merge request memri/pymemri!28
parents b5f7e57a e783a764
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docs/plugin.pluginbase.html
+ 11
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......@@ -50,8 +50,7 @@ nb_path: "nbs/plugin.pluginbase.ipynb"
<div class="inner_cell">
<div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># # hide</span>
<span class="c1"># class PluginSettings(Item):</span>
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># class PluginSettings(Item):</span>
<span class="c1"># def __init__(self, settings_dict):</span>
<span class="c1"># self.settings_dict=settings_dict</span>
......@@ -177,23 +176,6 @@ nb_path: "nbs/plugin.pluginbase.ipynb"
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="inner_cell">
<div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">assert</span> <span class="n">client</span><span class="o">.</span><span class="n">add_to_schema</span><span class="p">(</span><span class="n">PluginRun</span><span class="p">(</span><span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="s2">&quot;&quot;</span><span class="p">))</span>
</pre></div>
</div>
</div>
</div>
</div>
{% endraw %}
{% raw %}
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="inner_cell">
<div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span>
......@@ -213,58 +195,11 @@ nb_path: "nbs/plugin.pluginbase.ipynb"
<div class="inner_cell">
<div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># client.create(plugin)</span>
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">assert</span> <span class="n">client</span><span class="o">.</span><span class="n">add_to_schema</span><span class="p">(</span><span class="n">PluginRun</span><span class="p">(</span><span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="s2">&quot;&quot;</span><span class="p">))</span>
<span class="c1"># client.create(plugin)</span>
<span class="n">run</span> <span class="o">=</span> <span class="n">PluginRun</span><span class="p">(</span><span class="s2">&quot;pymemri&quot;</span><span class="p">,</span> <span class="s2">&quot;pymemri.plugin.pluginbase&quot;</span><span class="p">,</span> <span class="s2">&quot;MyPlugin&quot;</span><span class="p">,</span> <span class="s2">&quot;my_config_string&quot;</span><span class="p">)</span>
</pre></div>
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{% endraw %}
{% raw %}
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="inner_cell">
<div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">client</span><span class="o">.</span><span class="n">create</span><span class="p">(</span><span class="n">run</span><span class="p">)</span>
</pre></div>
</div>
</div>
</div>
<div class="output_wrapper">
<div class="output">
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<div class="output_text output_subarea output_execute_result">
<pre>True</pre>
</div>
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{% raw %}
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="inner_cell">
<div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">run</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">run</span><span class="o">.</span><span class="n">id</span><span class="p">)</span>
<span class="k">assert</span> <span class="n">client</span><span class="o">.</span><span class="n">create</span><span class="p">(</span><span class="n">run</span><span class="p">)</span>
<span class="n">run</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">run</span><span class="o">.</span><span class="n">id</span><span class="p">)</span>
</pre></div>
</div>
......@@ -318,7 +253,7 @@ nb_path: "nbs/plugin.pluginbase.ipynb"
<div class="output_markdown rendered_html output_subarea ">
<h4 id="run_plugin" class="doc_header"><code>run_plugin</code><a href="https://gitlab.memri.io/memri/pymemri/tree/prod/pymemri/plugin/pluginbase.py#L166" class="source_link" style="float:right">[source]</a></h4><blockquote><p><code>run_plugin</code>(<strong><code>pod_full_address</code></strong>:<code>Param object at 0x7f99922dd310&gt;</code>=<em><code>None</code></em>, <strong><code>plugin_run_id</code></strong>:<code>Param object at 0x7f99922dd390&gt;</code>=<em><code>None</code></em>, <strong><code>database_key</code></strong>:<code>Param object at 0x7f9990eba450&gt;</code>=<em><code>None</code></em>, <strong><code>owner_key</code></strong>:<code>Param object at 0x7f9990fb6650&gt;</code>=<em><code>None</code></em>, <strong><code>container</code></strong>:<code>Param object at 0x7f998f30a110&gt;</code>=<em><code>None</code></em>)</p>
<h4 id="run_plugin" class="doc_header"><code>run_plugin</code><a href="https://gitlab.memri.io/memri/pymemri/tree/prod/pymemri/plugin/pluginbase.py#L166" class="source_link" style="float:right">[source]</a></h4><blockquote><p><code>run_plugin</code>(<strong><code>pod_full_address</code></strong>:<code>Param object at 0x7fe4f89c6340&gt;</code>=<em><code>None</code></em>, <strong><code>plugin_run_id</code></strong>:<code>Param object at 0x7fe4f89c63d0&gt;</code>=<em><code>None</code></em>, <strong><code>database_key</code></strong>:<code>Param object at 0x7fe4f89c6370&gt;</code>=<em><code>None</code></em>, <strong><code>owner_key</code></strong>:<code>Param object at 0x7fe4f03fcd60&gt;</code>=<em><code>None</code></em>, <strong><code>container</code></strong>:<code>Param object at 0x7fe4f03fcd30&gt;</code>=<em><code>None</code></em>)</p>
</blockquote>
</div>
......@@ -368,8 +303,8 @@ nb_path: "nbs/plugin.pluginbase.ipynb"
<div class="output_subarea output_stream output_stdout output_text">
<pre>Used arguments passed to `run_plugin()` (ignoring environment)
pod_full_address=http://localhost:3030
plugin_run_id=33A294a95F9dE405DB7548ccf7AA6CA5
owner_key=0976404262528527457330449252813526842102910066371174763451992320
plugin_run_id=F43eAc940247d0c4d489CCF2b5E0B1f5
owner_key=9854591174276213062733795227026794332668461183308916489580798898
auth_json=None
running
......@@ -418,7 +353,7 @@ running
<div class="output_markdown rendered_html output_subarea ">
<h4 id="run_plugin_from_pod" class="doc_header"><code>run_plugin_from_pod</code><a href="https://gitlab.memri.io/memri/pymemri/tree/prod/pymemri/plugin/pluginbase.py#L198" class="source_link" style="float:right">[source]</a></h4><blockquote><p><code>run_plugin_from_pod</code>(<strong><code>pod_full_address</code></strong>:"The pod full address"=<em><code>None</code></em>, <strong><code>database_key</code></strong>:"Database key of the pod"=<em><code>None</code></em>, <strong><code>owner_key</code></strong>:"Owner key of the pod"=<em><code>None</code></em>, <strong><code>container</code></strong>:"Pod container to run frod"=<em><code>None</code></em>, <strong><code>plugin_module</code></strong>:"Plugin module"=<em><code>None</code></em>, <strong><code>plugin_name</code></strong>:"Plugin class name"=<em><code>None</code></em>)</p>
<h4 id="run_plugin_from_pod" class="doc_header"><code>run_plugin_from_pod</code><a href="https://gitlab.memri.io/memri/pymemri/tree/prod/pymemri/plugin/pluginbase.py#L198" class="source_link" style="float:right">[source]</a></h4><blockquote><p><code>run_plugin_from_pod</code>(<strong><code>pod_full_address</code></strong>:"The pod full address"=<em><code>None</code></em>, <strong><code>database_key</code></strong>:"Database key of the pod"=<em><code>None</code></em>, <strong><code>owner_key</code></strong>:"Owner key of the pod"=<em><code>None</code></em>, <strong><code>container</code></strong>:"Pod container to run frod"=<em><code>None</code></em>, <strong><code>plugin_module</code></strong>:"Plugin module"=<em><code>None</code></em>, <strong><code>plugin_name</code></strong>:"Plugin class name"=<em><code>None</code></em>, <strong><code>settings_file</code></strong>:"Plugin settings (json)"=<em><code>None</code></em>)</p>
</blockquote>
</div>
......@@ -468,9 +403,9 @@ running
<div class="output_subarea output_stream output_stdout output_text">
<pre>pod_full_address=http://localhost:3030
owner_key=0976404262528527457330449252813526842102910066371174763451992320
owner_key=9854591174276213062733795227026794332668461183308916489580798898
calling the `create` api on http://localhost:3030 to make your Pod start a plugin with id e6FD5D4Fbacf052A250A729EBc9e60db.
calling the `create` api on http://localhost:3030 to make your Pod start a plugin with id d6cF8fEc7A94F1Fc02dbD7bDaAa1c3FE.
*Check the pod log/console for debug output.*
</pre>
</div>
......
nbs/plugin.pluginbase.ipynb
+ 9
- 19
View file @ 12d17835
%% Cell type:code id: tags:
``` python
%load_ext autoreload
%autoreload 2
# default_exp plugin.pluginbase
```
%% Output
The autoreload extension is already loaded. To reload it, use:
%reload_ext autoreload
%% Cell type:code id: tags:
``` python
# export
from pymemri.data.schema import *
from pymemri.pod.client import PodClient, DEFAULT_POD_ADDRESS
from pymemri.imports import *
from os import environ
from abc import ABCMeta
import abc
import json
import importlib
import string
```
%% Cell type:code id: tags:
``` python
# hide
from nbdev.showdoc import *
```
%% Cell type:markdown id: tags:
# Plugins
%% Cell type:code id: tags:
``` python
# export
POD_FULL_ADDRESS_ENV = 'POD_FULL_ADDRESS'
POD_TARGET_ITEM_ENV = 'POD_TARGET_ITEM'
POD_OWNER_KEY_ENV = 'POD_OWNER'
POD_AUTH_JSON_ENV = 'POD_AUTH_JSON'
```
%% Cell type:code id: tags:
``` python
# # hide
# class PluginSettings(Item):
# def __init__(self, settings_dict):
# self.settings_dict=settings_dict
# def __getattr__(self, k):
# if k in self.settings_dict:
# return self.settings_dict[k]
# @classmethod
# def from_string(cls, s):
# objs = json.loads(s)
# cls(objs)
```
%% Cell type:code id: tags:
``` python
# export
# hide
class PluginBase(Item, metaclass=ABCMeta):
"""Base class for plugins"""
properties = Item.properties + ["name", "repository", "icon", "data_query", "bundleImage",
"runDestination", "pluginClass"]
edges = Item.edges + ["PluginRun"]
def __init__(self, name=None, repository=None, icon=None, query=None, bundleImage=None, runDestination=None,
pluginClass=None, indexerRun=None, **kwargs):
if pluginClass is None: pluginClass=self.__class__.__name__
super().__init__(**kwargs)
self.name = name
self.repository = repository
self.icon = icon
self.query = query
self.bundleImage = bundleImage
self.runDestination = runDestination
self.pluginClass = pluginClass
self.indexerRun = indexerRun if indexerRun is not None else []
@abc.abstractmethod
def run(self):
raise NotImplementedError()
@abc.abstractmethod
def add_to_schema(self):
raise NotImplementedError()
```
%% Cell type:code id: tags:
``` python
# export
# hide
class PluginRun(Item):
properties = Item.properties + ["targetItemId", "pluginModule", "pluginName", "config", "containerImage"]
edges = PluginBase.edges
def __init__(self, containerImage, pluginModule, pluginName, config="",targetItemId=None, **kwargs):
"""
PluginRun defines a the run of plugin `plugin_module.plugin_name`,
with an optional `config` string.
Args:
plugin_module (str): module of the plugin.
plugin_name (str): class name of the plugin.
config (str, optional): Optional plugin configuration. For example,
this could be a `json.dumps` of a configuration dict. Defaults to None.
"""
super().__init__(**kwargs)
self.pluginModule = pluginModule
self.pluginName = pluginName
self.config = config
self.containerImage=containerImage
id_ = "".join([random.choice(string.hexdigits) for i in range(32)]) if targetItemId is None else targetItemId
self.targetItemId=id_
self.id=id_
```
%% Cell type:markdown id: tags:
## Creating a plugin
%% Cell type:markdown id: tags:
The memri [pod](https://gitlab.memri.io/memri/pod) uses a plugin system to add features to the backend memri backend. Plugins, can import your data (importers), change your data (indexers), or call other serivces. Users can define their own plugins to add new behaviour to their memri app. Let's use the following plugin as an example of how we can start plugins.
%% Cell type:code id: tags:
``` python
# export
# hide
class MyItem(Item):
properties = Item.properties + ["name", "age"]
edges = Item.edges
def __init__(self, name=None, age=None, **kwargs):
super().__init__(**kwargs)
self.name = name
self.age = age
class MyPlugin(PluginBase):
""""""
properties = PluginBase.properties + ["containerImage"]
edges= PluginBase.edges
def __init__(self, **kwargs):
super().__init__(**kwargs)
def run(self, run, client):
print("running")
client.create(MyItem("some person", 20))
def add_to_schema(self, client):
client.add_to_schema(MyItem("my name", 10))
```
%% Cell type:markdown id: tags:
Memri plugins need to define at least 2 methods: `.run()` and `.add_to_schema()`. `.run()` defines the logic of the plugin. `.add_to_schema()` defines the schema for the plugin in the pod. Note that currently, `add_to_schema` requires all item to **have all properties defined that are used in the plugin**. In the future, we might replace add_to_schema, to be done automatically, based on a declarative schema defined in the plugin.
%% Cell type:code id: tags:
``` python
MyPlugin()
```
%% Output
MyPlugin (#None)
%% Cell type:markdown id: tags:
```python
class MyItem(Item):
properties = Item.properties + ["name", "age"]
edges = Item.edges
def __init__(self, name=None, age=None, **kwargs):
super().__init__(**kwargs)
self.name = name
self.age = age
class MyPlugin(PluginBase):
""""""
properties = PluginBase.properties
edges= PluginBase.edges
def __init__(self, **kwargs):
super().__init__(**kwargs)
def run(self, run, client):
print("running")
client.create(MyItem("some person", 20))
def add_to_schema(self, client):
client.add_to_schema(MyItem("my name", 10))
```
%% Cell type:code id: tags:
``` python
from pymemri.pod.client import PodClient
client = PodClient()
```
%% Cell type:code id: tags:
``` python
# assert client.add_to_schema(Plugin("", "", "", "", "", "", "", ""))
```
%% Cell type:code id: tags:
``` python
# skip
assert client.add_to_schema(PluginRun("", "", "", "", ""))
# client.create(plugin)
run = PluginRun("pymemri", "pymemri.plugin.pluginbase", "MyPlugin", "my_config_string")
assert client.create(run)
run = client.get(run.id)
```
%% Cell type:markdown id: tags:
## Running your plugin
%% Cell type:markdown id: tags:
Plugins can be started using the pymemri `run_plugin` CLI. To use the CLI, you can either pass your run arguments as parameters, or set them as environment variables. If both are set, the CLI will prefer the passed arguments.
%% Cell type:code id: tags:
``` python
# hide
# export
def get_plugin(plugin_module, plugin_name):
try:
module = importlib.import_module(plugin_module)
plugin_cls = getattr(module, plugin_name)
return plugin_cls()
except (ImportError, AttributeError):
raise ImportError(f"Unknown plugin: {plugin_module}.{plugin_name}")
def run_plugin_from_run_id(run_id, client, return_plugin=False):
"""
Args:
run_id (int): id of the PluginRun
client (PodClient): client containing PluginRun
return_plugin (bool): Returns created plugin instance for testing purposes.
"""
run = client.get(run_id)
plugin = get_plugin(run.pluginModule, run.pluginName)
plugin.add_to_schema(client)
plugin.run(run, client)
return plugin if return_plugin else None
```
%% Cell type:code id: tags:
``` python
# export
# hide
def register_base_classes(client):
def register_base_schemas(client):
try:
assert client.add_to_schema(PluginRun("", "", "", "", ""))
except Exception as e:
raise ValueError("Could not add base schema")
```
%% Cell type:code id: tags:
``` python
# hide
# skip
run_plugin_from_run_id(run.id, client)
```
%% Output
running
%% Cell type:code id: tags:
``` python
# export
def _run_plugin(client, plugin_run_id=None, verbose=False):
"""Runs an plugin, you can either provide the run settings as parameters to this function (for local testing)
or via environment variables (this is how the pod communicates with plugins)."""
register_base_classes(client)
register_base_schemas(client)
run_plugin_from_run_id(plugin_run_id, client)
```
%% Cell type:code id: tags:
``` python
# hide
# skip
_run_plugin(client=client, plugin_run_id=run.id)
```
%% Output
running
%% Cell type:markdown id: tags:
### CLI
%% Cell type:code id: tags:
``` python
# export
# hide
def _parse_env(env):
try:
pod_full_address = env.get(POD_FULL_ADDRESS_ENV, DEFAULT_POD_ADDRESS)
plugin_run_json = json.loads(str(env[POD_TARGET_ITEM_ENV]))
print(plugin_run_json)
plugin_run_id = plugin_run_json["id"]
owner_key = env.get(POD_OWNER_KEY_ENV)
pod_auth_json = json.loads(str(env.get(POD_AUTH_JSON_ENV)))
# database_key = pod_service_payload[DATABASE_KEY_ENV]
# owner_key = pod_service_payload[OWNER_KEY_ENV]
return pod_full_address, plugin_run_id, pod_auth_json, owner_key
except KeyError as e:
raise Exception('Missing parameter: {}'.format(e)) from None
```
%% Cell type:code id: tags:
``` python
# export
from fastscript import *
import os
```
%% Cell type:code id: tags:
``` python
# export
@call_parse
def run_plugin(pod_full_address:Param("The pod full address", str)=None,
plugin_run_id:Param("Run id of the plugin to be executed", str)=None,
database_key:Param("Database key of the pod", str)=None,
owner_key:Param("Owner key of the pod", str)=None,
container:Param("Pod container to run frod", str)=None):
env = os.environ
params = [pod_full_address, plugin_run_id, database_key, owner_key]
if all([p is None for p in params]):
print("Reading `run_plugin()` parameters from environment variables")
pod_full_address, plugin_run_id, pod_auth_json, owner_key = _parse_env(env)
database_key=None
else:
print("Used arguments passed to `run_plugin()` (ignoring environment)")
pod_auth_json=None
if (None in params):
raise ValueError(f"Defined some params to run indexer, but not all. Missing \
{[p for p in params if p is None]}")
client = PodClient(url=pod_full_address, database_key=database_key, owner_key=owner_key,
auth_json=pod_auth_json)
for name, val in [("pod_full_address", pod_full_address), ("plugin_run_id", plugin_run_id),
("owner_key", owner_key), ("auth_json", pod_auth_json)]:
print(f"{name}={val}")
print()
_run_plugin(client=client, plugin_run_id=plugin_run_id)
```
%% Cell type:markdown id: tags:
To start a plugin on your local machine, you can use the CLI. This will create a client for you, and run the code defined in `<myplugin>.run()`
%% Cell type:code id: tags:
``` python
!run_plugin --pod_full_address=$DEFAULT_POD_ADDRESS --owner_key=$client.owner_key \
--database_key=$client.database_key --container="pymemri" --plugin_run_id=$run.id
```
%% Output
Used arguments passed to `run_plugin()` (ignoring environment)
pod_full_address=http://localhost:3030
plugin_run_id=eA8449C3691deFB7fBFBEdCEB2Aa638b
owner_key=5425376981118796856269853197369070143735402057204813973167558395
plugin_run_id=F43eAc940247d0c4d489CCF2b5E0B1f5
owner_key=9854591174276213062733795227026794332668461183308916489580798898
auth_json=None
running
%% Cell type:markdown id: tags:
## Run plugin from pod -
%% Cell type:code id: tags:
``` python
# # export
# # hide
# class StartPlugin(Item):
# properties = Item.properties + ["container", "targetItemId"]
# edges = Item.edges
# def __init__(self, container=None, targetItemId=None, **kwargs):
# super().__init__(**kwargs)
# self.container = container
# self.targetItemId = targetItemId
```
%% Cell type:code id: tags:
``` python
# export
from fastcore.script import call_parse, Param
import os
@call_parse
def run_plugin_from_pod(pod_full_address:Param("The pod full address", str)=None,
database_key:Param("Database key of the pod", str)=None,
owner_key:Param("Owner key of the pod", str)=None,
container:Param("Pod container to run frod", str)=None,
plugin_module:Param("Plugin module", str)=None,
plugin_name:Param("Plugin class name", str)=None,
settings_file:Param("Plugin settings (json)", str)=None):
params = [pod_full_address, database_key, owner_key, container, plugin_module, plugin_name]
if (None in params):
raise ValueError(f"Defined some params to run indexer, but not all. Missing \
{[p for p in params if p is None]}")
client = PodClient(url=pod_full_address, database_key=database_key, owner_key=owner_key)
for name, val in [("pod_full_address", pod_full_address), ("owner_key", owner_key)]:
print(f"{name}={val}")
if settings_file is not None:
with open(settings_file, 'r') as f:
settings = f.read()
print(type(settings))
print(settings)
else:
settings = None
run = PluginRun(container, plugin_module, plugin_name, "settings")
register_base_schemas(client)
run = PluginRun(container, plugin_module, plugin_name, settings)
print(f"\ncalling the `create` api on {pod_full_address} to make your Pod start "
f"a plugin with id {run.id}.")
print(f"*Check the pod log/console for debug output.*")
client.create(run)
```
%% Cell type:markdown id: tags:
In production, we start plugins by making an API call to the pod, which in turn creates an environment for the plugin and starts it (currently on docker is supported). We can start this process using the CLI by provding `--from_pod==True` and providing a `--container` (the docker container used by the pod). **Note that the provided docker container should be installed within the Pod environemnt (e.g. `docker build -t pymemri .` for this repo) in order to start it.**
%% Cell type:code id: tags:
``` python
!run_plugin_from_pod --pod_full_address=$DEFAULT_POD_ADDRESS --owner_key=$client.owner_key \
--database_key=$client.database_key --container="pymemri" \
--plugin_module="pymemri.plugin.pluginbase" --plugin_name="MyPlugin"
```
%% Output
pod_full_address=http://localhost:3030
owner_key=5425376981118796856269853197369070143735402057204813973167558395
owner_key=9854591174276213062733795227026794332668461183308916489580798898
calling the `create` api on http://localhost:3030 to make your Pod start a plugin with id 637ac2a4b5Dbf78c2b48D201CfBC0E2f.
calling the `create` api on http://localhost:3030 to make your Pod start a plugin with id d6cF8fEc7A94F1Fc02dbD7bDaAa1c3FE.
*Check the pod log/console for debug output.*
%% Cell type:markdown id: tags:
> Note: The data that was created earlier (PluginRun, plugin) should be in the pod in order for this to work
%% Cell type:code id: tags:
``` python
# hide
# client.start_plugin("pymemri", run.id)
```
%% Cell type:markdown id: tags:
## Running a Plugin by providing environment variables -
%% Cell type:code id: tags:
``` python
# hide
# # export
# def generate_test_env(client, indexer_run):
# payload = json.dumps({DATABASE_KEY_ENV: client.database_key, OWNER_KEY_ENV: client.owner_key})
# return {POD_FULL_ADDRESS_ENV: DEFAULT_POD_ADDRESS,
# POD_TARGET_ITEM: indexer_run.id,
# POD_SERVICE_PAYLOAD_ENV: payload}
```
%% Cell type:code id: tags:
``` python
# hide
# run_plugin(env=generate_test_env(client, run))
```
%% Cell type:markdown id: tags:
# Export -
%% Cell type:code id: tags:
``` python
# hide
from nbdev.export import *
notebook2script()
```
%% Output
Converted basic.ipynb.
Converted data.photo.ipynb.
Converted importers.Importer.ipynb.
Converted importers.util.ipynb.
Converted index.ipynb.
Converted indexers.indexer.ipynb.
Converted itembase.ipynb.
Converted plugin.pluginbase.ipynb.
Converted pod.client.ipynb.
%% Cell type:code id: tags:
``` python
```
......
pymemri/_nbdev.py
+ 1
- 1
View file @ 12d17835
......@@ -48,7 +48,7 @@ index = {"read_file": "basic.ipynb",
"MyPlugin": "plugin.pluginbase.ipynb",
"get_plugin": "plugin.pluginbase.ipynb",
"run_plugin_from_run_id": "plugin.pluginbase.ipynb",
"register_base_classes": "plugin.pluginbase.ipynb",
"register_base_schemas": "plugin.pluginbase.ipynb",
"run_plugin": "plugin.pluginbase.ipynb",
"run_plugin_from_pod": "plugin.pluginbase.ipynb",
"DEFAULT_POD_ADDRESS": "pod.client.ipynb",
......
pymemri/plugin/pluginbase.py
+ 5
- 6
View file @ 12d17835
# AUTOGENERATED! DO NOT EDIT! File to edit: nbs/plugin.pluginbase.ipynb (unless otherwise specified).
__all__ = ['POD_FULL_ADDRESS_ENV', 'POD_TARGET_ITEM_ENV', 'POD_OWNER_KEY_ENV', 'POD_AUTH_JSON_ENV', 'PluginBase',
'PluginRun', 'MyItem', 'MyPlugin', 'get_plugin', 'run_plugin_from_run_id', 'register_base_classes',
'PluginRun', 'MyItem', 'MyPlugin', 'get_plugin', 'run_plugin_from_run_id', 'register_base_schemas',
'run_plugin', 'run_plugin_from_pod']
# Cell
......@@ -127,7 +127,7 @@ def run_plugin_from_run_id(run_id, client, return_plugin=False):
# Cell
# hide
def register_base_classes(client):
def register_base_schemas(client):
try:
assert client.add_to_schema(PluginRun("", "", "", "", ""))
except Exception as e:
......@@ -137,7 +137,7 @@ def register_base_classes(client):
def _run_plugin(client, plugin_run_id=None, verbose=False):
"""Runs an plugin, you can either provide the run settings as parameters to this function (for local testing)
or via environment variables (this is how the pod communicates with plugins)."""
register_base_classes(client)
register_base_schemas(client)
run_plugin_from_run_id(plugin_run_id, client)
......@@ -214,12 +214,11 @@ def run_plugin_from_pod(pod_full_address:Param("The pod full address", str)=None
if settings_file is not None:
with open(settings_file, 'r') as f:
settings = f.read()
print(type(settings))
print(settings)
else:
settings = None
run = PluginRun(container, plugin_module, plugin_name, "settings")
register_base_schemas(client)
run = PluginRun(container, plugin_module, plugin_name, settings)
print(f"\ncalling the `create` api on {pod_full_address} to make your Pod start "
f"a plugin with id {run.id}.")
print(f"*Check the pod log/console for debug output.*")
......
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